Current strategies for mutation detection in phenotype-driven screens utilising next generation sequencing.

Area of Science:

• Genetics and Genomics
• Molecular Biology
• Disease Modeling

Background:

• Mutagenesis screens in mice are vital for identifying novel genes linked to disease phenotypes.
• N-ethyl-N-nitrosourea (ENU) mutagenesis induces random single nucleotide variants in the mouse genome.
• Unbiased phenotyping identifies mutated pathways without prior knowledge of gene function.

Purpose of the Study:

• To describe strategies for identifying ENU variants using next-generation sequencing (NGS) data.
• To outline subsequent steps for mutation characterization in ENU screens.
• To highlight the impact of NGS on accelerating ENU-based gene discovery.

Main Methods:

• Utilizing N-ethyl-N-nitrosourea (ENU) for random mutagenesis in mice.
• Employing next-generation sequencing (NGS) for variant identification.
• Implementing phenotyping assays to link mutations to disease phenotypes.

Main Results:

• Next-generation sequencing (NGS) has transformed ENU variant identification from a laborious task to a rapid process.
• Three distinct strategies for identifying ENU variants from NGS data are presented.
• The study facilitates high-throughput mutation discovery in large mouse facilities.

Conclusions:

• ENU mutagenesis screens coupled with NGS are powerful tools for accelerating basic science and mechanistic research.
• Efficient ENU variant identification is crucial for characterizing gene function in disease.
• Advances in sequencing technology have significantly improved the efficiency of ENU-based discovery platforms.